Results 11 to 20 of about 4,822,114 (362)
VIRTUALLY THROWING BENCHMARKS INTO THE OCEAN FOR DEEP SEA PHOTOGRAMMETRY AND IMAGE PROCESSING EVALUATION [PDF]
ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2022 Vision in the deep sea is acquiring increasing interest from many fields as the deep seafloor represents the largest surface portion on Earth. Unlike common shallow underwater imaging, deep sea imaging requires artificial lighting to illuminate the scene
Y. Song, M. She, K. Köser
doaj +1 more source
Open Research Europe, 2022 To overcome the data scarcity problem of machine learning for nondestructive testing, data augmentation is a commonly used strategy. We propose a method to enable training of neural networks exclusively on simulated data.
Klaus Schlachter +2 more
doaj +1 more source
CVML-Pose: Convolutional VAE Based Multi-Level Network for Object 3D Pose Estimation
IEEE Access, 2023 Most vision-based 3D pose estimation approaches typically rely on knowledge of object’s 3D model, depth measurements, and often require time-consuming iterative refinement to improve accuracy.
Jianyu Zhao +2 more
doaj +1 more source
Electronics Letters, 2023 Deep learning models have been widely applied in video‐based depression detection. It is observed that the diversity of preprocessing, data augmentation, and optimization techniques makes it difficult to fairly compare model architectures. In this study,
Manuel Lage Cañellas +3 more
doaj +1 more source
State of the Art in Defect Detection Based on Machine Vision
International Journal of Precision Engineering and Manufacturing - Green Technology, 2021 Machine vision significantly improves the efficiency, quality, and reliability of defect detection. In visual inspection, excellent optical illumination platforms and suitable image acquisition hardware are the prerequisites for obtaining high-quality ...
Zhonghe Ren, F. Fang, Ning Yan, You Wu
semanticscholar +1 more source
Dynamic machine vision with retinomorphic photomemristor-reservoir computing
Nature Communications, 2023 Dynamic machine vision requires recognizing the past and predicting the future of a moving object based on present vision. Current machine vision systems accomplish this by processing numerous image frames or using complex algorithms.
Hongwei Tan, S. van Dijken
semanticscholar +1 more source
Ultrafast dynamic machine vision with spatiotemporal photonic computing
Science Advances, 2023 Ultrafast dynamic machine vision in the optical domain can provide unprecedented perspectives for high-performance computing. However, owing to the limited degrees of freedom, existing photonic computing approaches rely on the memory’s slow read/write ...
Tiankuang Zhou +4 more
semanticscholar +1 more source
Fast Light Field Angular Resolution Enhancement Using Convolutional Neural Network
IEEE Access, 2021 Current light field angular super-resolution algorithm based on deep learning has excessive computation cost and low operational efficiency, for sequentially up-sampling on each lenslet region of the light field image.
Xingzheng Wang +3 more
doaj +1 more source
Fruit Sizing in Orchard: A Review from Caliper to Machine Vision with Deep Learning
Italian National Conference on Sensors, 2023 Forward estimates of harvest load require information on fruit size as well as number. The task of sizing fruit and vegetables has been automated in the packhouse, progressing from mechanical methods to machine vision over the last three decades.
C. Neupane +3 more
semanticscholar +1 more source
Towards Machine Vision for Insect Welfare Monitoring and Behavioural Insights
Frontiers in Veterinary Science, 2022 Machine vision has demonstrated its usefulness in the livestock industry in terms of improving welfare in such areas as lameness detection and body condition scoring in dairy cattle. In this article, we present some promising results of applying state of
Mark F. Hansen +5 more
doaj +1 more source